Table 3 Reasons and questions that call for mixing methods to examine feasibility domains
From: Applying mixed methods to pilot feasibility studies to inform intervention trials
Common reasons for mixing methods | Example mixed methods data integration questions | |
|---|---|---|
General examples | Specific examples | |
Triangulation: need to compare quantitative and qualitative evidence to identify areas of corroboration and dissonance to inform a robust decision about feasibility | To what extent and in what ways is (domain of concern) feasible? | How do participant ratings of intervention acceptability compare to what they say about their satisfaction with the intervention? |
Completeness: need to synthesize quantitative and qualitative information about different facets of feasibility to develop a comprehensive understanding of feasibility | What is the feasibility in terms of (domain of concern) and what barriers need to be addressed? | What recruitment barriers are identified when recruitment rates are combined with participants’ experience of the recruitment process? |
Explanation: need to interconnect quantitative and qualitative information to uncover and explain differences in feasibility for subgroups or contexts | Does (domain of concern) differ for (subgroups or contexts of interest) and, if so, why? | What are intervention fidelity ratings by study site and why are ratings high, average, and/or low? |